Get error from proxy.error.var object

Usage

GetProxyError(
  var.obj,
  timescale,
  exclude = NULL,
  include.f.zero = TRUE,
  format = "long"
)

Arguments

var.obj: timescale dependent variance object from IntegrateErrorSpectra
timescale: the temporal resolution at which the proxy values are being interpreted
exclude: character vector of error components to exclude from the total
include.f.zero: include or exclude power at nu = 0
format: format of the output

Value

1 row dataframe with 1 SD error components

Examples

spec.pars <- GetSpecPars("Mg_Ca", tau_p = 1 / 12, phi_c = 0, seas.amp = 4, T = 100 * 101)
spec.obj <- do.call(ProxyErrorSpectrum, spec.pars)
#> Warning: Rounding T to 10100 so that T is an odd integer multiple of delta_t
PlotSpecError(spec.obj)
#> Warning: There were 4 warnings in `summarise()`.
#> The first warning was:
#> ℹ In argument: `max.spec = max(spec, na.rm = TRUE)`.
#> ℹ In group 9: `component = "Climate"` and `ax.grp = "nu == 0"`.
#> Caused by warning in `max()`:
#> ! no non-missing arguments to max; returning -Inf
#> ℹ Run `dplyr::last_dplyr_warnings()` to see the 3 remaining warnings.
#> Joining with `by = join_by(component, ax.grp)`
#> Warning: log-10 transformation introduced infinite values.
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?

var.obj <- IntegrateErrorSpectra(spec.obj)
PlotTSDVariance(var.obj)
#> Warning: Removed 8 rows containing non-finite outside the scale range (`stat_align()`).

GetProxyError(var.obj, timescale = 100)
#>    smoothed.resolution            component       f.zero  inc.f.zero
#> 1                  100    Aliasing.seasonal 0.0003928943 0.003948539
#> 2                  100  Aliasing.stochastic 0.0251216653 0.252469612
#> 3                  100         Bioturbation 0.0000000000 0.525258573
#> 4                  100     Calibration.unc. 0.3000000000 0.300000000
#> 5                  100 Individual.variation 0.0273861279 0.275227179
#> 6                  100           Meas.error 0.0260000000 0.261296766
#> 7                  100    Reference.climate           NA 0.927987688
#> 8                  100        Seasonal.bias 1.9772250389 1.980631450
#> 9                  100   Seasonal.bias.unc. 0.0000000000 0.000000000
#> 10                 100          Total.error 2.0003689927 2.120514090
#>     exl.f.zero
#> 1  0.003928943
#> 2  0.251216653
#> 3  0.525258573
#> 4  0.000000000
#> 5  0.273861279
#> 6  0.260000000
#> 7           NA
#> 8  0.116112383
#> 9  0.000000000
#> 10 0.703636197